The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Most clinical measurements rely on bioelectromagnetic phenomena. These events allow us to record electric or magnetic signals during the activity of living tissues. In this paper, we put our attention on the bioelectric fields that occur in the muscle activity. In fact during the body movements, the muscle contractions produce a bioelectric potential distribution that can be measured by putting the...
An EMG-driven arm wrestling robot (AWR) is being developed in our laboratories for the purposes of studying neuromuscular control of arm movements. The AWR arm have 2-DOF, integrated with mechanical arm, elbow/wrist force sensors, servo motor, encoder, 3-D MEMS accelerometer, and USB camera, is used to estimate tension developed by individual muscles based on recorded electromyograms (EMGs). The surface...
A five-fingered underactuated prosthetic hand controlled by surface electromyographic (EMG) signals is presented in this paper. The prosthetic hand control part is based on an EMG motion pattern classifier which combines Levenberg-Marquardt (LM) or variable learning rate (VLR) based neural network with parametric autoregressive (AR) model and wavelet transform. This motion pattern classifier can successfully...
Electromyography (EMG) became noisy in the collection and transmission. To eliminate the noise, a novel threshold value method based on the wavelet de-noise was proposed. Firstly, the obtained EMG signal was decomposed by the wavelet transform. Then, the decomposed wavelet coefficients were analysed by the weighted average of traditional soft-threshold and hard-threshold. Finally, the wavelet coefficients...
This paper presents a novel 2 DOF robotic arm wrestling system integrated with mechanical arm, elbow/wrist force sensors, servo motor, encoder, 3-D MEMS accelerometer, and USB camera. The arm wrestling robot (AWR) is used to play arm wrestling game with human for entertainment. Based on the force testing equipment, we acquire the data of surface electromyographic (EMG) signals form target muscle when...
A five-fingered underactuated prosthetic hand controlled by surface EMG (electromyographic) signals is presented in this paper. The prosthetic hand is designed with simplicity, lightweight and dexterity on the requirement of anthropomorphic hands. Underactuated self-adaptive theory is adopted to decrease the number of motors and weight. The fingers of the hand with multi phalanges have the same size...
A new five-fingered underactuated prosthetic hand control system is presented in this paper. The prosthetic hand control part is based on an EMG motion pattern classifier which combines VLR (variable learning rate) based neural network with wavelet transform and sample entropy. This motion pattern classifier can successfully identify flexion and extension of the thumb, the index finger and the middle...
In this paper, we develop a novel robotic arm wrestling system integrated with mechanical arm, elbow/wrist force sensors, servo motor, encoder, 3-D MEMS accelerometer, and USB camera. The arm wrestling robot (AWR) is intended to play arm wrestling game with real human on a table for entertainment. The designing scenario of the prototype model's hardware is performed. Elbow/wrist force sensors, as...
In this paper, the surface electromyographic (EMG) signals is acquired from the upper limb when the experimenter competes with the arm wrestling robot (AWR) which is integrated with mechanical arm, elbow/wrist force sensors, servo motor, encoder, 3D MEMS accelerometer, and USB camera. The arm wrestling robot (AWR) is intended to play arm wrestling game with human on a table with pegs for entertainment...
A system was previously designed to obtain estimates of the number of motor units (MUNE) in a superficial muscle and hence number of functioning motor neurons to that muscle. This method uses incremental stimulation of a motor nerve and subsequent recognition and classification of the elicited M-waves. In this earlier work we used the Fourier power coefficients as pattern classifiers. The presented...
This paper is concerned with the problem of localizing the typical features of a signal when it is observed with noise in order to align a set of curves. Structural intensity (SI) is a recent tool that computes the "density" of the location of the modulus maxima of a wavelet representation along various scales in order to identify singularities of an unknown signal. As a contribution to...
To date various signal processing techniques have been applied to surface electromyography (SEMG) for feature extraction and signal classification. Compared with traditional analysis methods which have been used in previous application, continuous wavelet transform (CWT) enhances the SEMG features more effectively. This paper presents methods of analysing SEMG signals using CWT and LabVIEW for extracting...
This paper reports research conducted to evaluate the use of sparse ICA for the separation of muscle activity from SEMG. It discusses some of the conditions that could affect the reliability of the separation and evaluates issues related to the properties of the signals and number of sources. The paper reports tests using Zibulevsky's method of temporal plotting to identify number of independent sources...
A system was previously designed to obtain estimates of the number of motor units (MUNE) in a superficial muscle and hence number of functioning motor neurons to that muscle. This method uses incremental stimulation of a motor nerve and subsequent recognition and classification of the elicited M-waves. In this earlier work we used the Fourier power coefficients as pattern classifiers. The presented...
This paper reports research conducted to evaluate the use of sparse ICA for the separation of muscle activity from SEMG. It discusses some of the conditions that could affect the reliability of the separation and evaluates issues related to the properties of the signals and number of sources. The paper reports tests using Zibulevsky's method of temporal plotting to identify number of independent sources...
The objective of this work was the study and the development of techniques for acquiring and processing electromyographic signals that can be used for analysis of the behavior of electromyographic variables during fatiguing dynamic activities. Two of the techniques were the RMS value and the MPF, which are commonly used for the analysis of electromyographic signals measured during isometric contractions...
EMG pattern recognition is essential for the control of a multifunction myoelectric hand. The main goal of this study is to develop an efficient feature projection method for EMG pattern recognition. To this end, we propose a linear supervised feature projection that utilizes linear discriminant analysis (LDA). We first perform wavelet packet transform (WPT) to extract the feature vector from four...
To date various signal processing techniques have been applied to surface electromyography (SEMG) for feature extraction and signal classification. Compared with traditional analysis methods which have been used in previous application, continuous wavelet transform (CWT) enhances the SEMG features more effectively. This paper presents methods of analysing SEMG signals using CWT and LabVIEW for extracting...
This study investigated the ability of vibromyography (VMG) to accurately represent voluntary forearm muscle contractile force during attempted-isometric contraction of the brachioradialis. VMG signals were collected from the brachioradialis of healthy adult men (mean age, 26.6plusmn9.8 years, N=24) during attempted-isometric contraction over a force range of 4.45 N to maximum sustained load. The...
This paper is concerned with the problem of localizing the typical features of a signal when it is observed with noise in order to align a set of curves. Structural intensity (SI) is a recent tool that computes the "density" of the location of the modulus maxima of a wavelet representation along various scales in order to identify singularities of an unknown signal. As a contribution to...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.